• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.817-825
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• 2016

In this paper, we introduce a flexible gripper that we have engineered to precisely pinch in parallel and compliantly grasp objects. As found in most conventional industrial grippers, the parallel pinching property is essential for precise manipulation. On the other hand, the grippers with a flexible structure are more adept at grasping objects with arbitrary shapes and softness. To achieve these disparate properties, we introduce a flexible gripper mechanism composed of multiple flexible beam structures. Utilizing these beam structures, the proposed gripper is able to grasp arbitrarily shaped objects. Additionally, a unique combination of flexible beams enables the gripper to pinch objects using the parallel fingertips for enhanced precision. A detailed description of the proposed mechanism is provided, and an analysis of the strength and stiffness of the fingertip and finger body is presented. The Results section compares the theoretical and experimental analyses and verifies the properties and performance of the proposed gripper.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.423-428
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• 2005

This paper proposes a new edge detection method using a $3{\times}3$ ideal binary pattern and lookup table (LUT) for the mobile robot localization without any parameter adjustments. We take the mean of the pixels within the $3{\times}3$ block as a threshold by which the pixels are divided into two groups. The edge magnitude and orientation are calculated by taking the difference of average intensities of the two groups and by searching directional code in the LUT, respectively. And also the input image is not only partitioned into multiple groups according to their intensity similarities by the histogram, but also the threshold of each group is determined by fuzzy reasoning automatically. Finally, the edges are determined through non-maximum suppression using edge confidence measure and edge linking. Applying this edge detection method to the mobile robot localization using projective invariance of the cross ratio. we demonstrate the robustness of the proposed method to the illumination changes in a corridor environment.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.4
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• pp.353-361
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• 2011

A precise embedded ultrasonic localization system is developed for autonomous mobile robots in indoor environments, which is essential for autonomous navigation of mobile robots with various tasks. Although ultrasonic sensors are more cost-effective than other sensors such as LRF (Laser Range Finder) and vision, they suffer inaccuracy and directional ambiguity. First, we apply the matched filter to measure the distance precisely. For resolving the computational complexity of the matched filter for embedded systems, we propose a new matched filter algorithm with fast computation in three points of view. Second, we propose an accurate ultrasonic localization system which consists of three ultrasonic receivers on the mobile robot and two or more transmitters on the ceiling. Last, we add an extended Kalman filter to estimate position and orientation. Various simulations and experimental results show the effectiveness of the proposed system.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.12
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• pp.1089-1093
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• 2013

Depth extraction using the structured illumination method is popularly applied since it has the benefit of measuring the object without contact. With multiple spatial frequencies and phase-shifting techniques, it is possible to extract the depth of objects with large discontinuity. For applications such as 3D (Three Dimensional) displays, 3D information of the object is required and is useful if corresponding to each view of the display. For this purpose, hypercentric optics is appropriate to measure the depth information of an object with a large field of view that is applicable for a 3D display. By experiment, we present the feasibility for phase-shifting profilometry using hypercentric optics to obtain the depth information of an object with the field of view appropriate for a 3D display.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.12
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• pp.1215-1219
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• 2006

Scheduling plays an important role in the process management in terms of providing profit-maximizing operation sequence of multiple orders and estimating completion times of them. In order to takes its full potential, varying conditions should be properly reflected in computing the schedule. The adjustment of scheduling decisions has to be made frequently in response to the occurrence of variations. It is often challenging because their model has to be adjusted and their solutions have to be computed within short time period. This paper employs Model Predictive Control(MPC) principles for updating the process condition in the scheduling model. The solutions of the resulting problems considering variations are computed using parametric programming techniques. The key advantage of the proposed framework is that repetition of solving similar programming problems with decreasing dimensionis avoided and all potential schedules are obtained before the execution of the actual processes. Therefore, the proposed framework contributes to constructing a robust decision-support tool in the face of varying environment. An example is solved to illustrate the potential of the proposed framework with remarks on potential wide applications.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.6
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• pp.602-612
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• 1997

With GPS carrier phase measurements from more than two antenna which attached to the vehicle, precise attitude can be easily obtained if the integer ambiguity included in carrier phase measurement is resolved. Recently some special products which use dual frequencies or has one receiver engine with multiple antenna are announced. But there are still strong requirements for the conventional single frequency off-the-shelf receiver. To meet these requirements, an efficient integer ambiguity resolution technique is indispensable. In this paper, a new technique to resolve integer imbiguity with single frequency receivers is proposed. The proposed method utilize the known baseline length as a constraint of independent elements of integer ambiguities. With this constraints, the size of search volume can be greatly reduced. Thus the true integer ambiguity can be easily determined with less computational burden and number of measurements. The proposed method is applied to real data to show its effectiveness.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.11
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• pp.1008-1016
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• 2015

This paper proposes a method for detecting the front side of vehicles. The method can find the car side with a license plate even with complicated and cluttered backgrounds. A convolutional neural network (CNN) is used to solve the detection problem as a unified framework combining feature detection, classification, searching, and localization estimation and improve the reliability of the system with simplicity of usage. The proposed CNN structure avoids sliding window search to find the locations of vehicles and reduces the computing time to achieve real-time processing. Multiple responses of the network for vehicle position are further processed by a weighted clustering and probabilistic threshold decision method. Experiments using real images in parking lots show the reliability of the method.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.237-242
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• 2012

AFC (Adaptive Feedforward Control) is significantly employed for improving control performance of dynamic systems particularly involving periodic disturbance signals in engineering fields. This paper presents a novel hybrid AFC approach for discrete-time systems with multiple disturbances in terms of control input and state variables. The proposed AFC mechanism is hierarchically composed of a conventional feedforward control framework and PID auxiliary control configuration in parallel. The former is generic to decrease periodic disturbance excited to control actuators and the latter is additionally constructed to overcome control deterioration due to time-varying uncertainty under given systems. We carry out numerical simulation to test reliability of our proposed hybrid AFC system and compare its control performance to a well-known conventional AFC method with respect to time and frequency domains for proving of its superiority.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.243-250
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• 2012

This paper proposes a 3D map-building algorithm using one LRF (Laser Range Finder) while a mobile robot is navigating on the slanted surface. There are several researches on 3D map buildings using the LRF. However most of them are performing the map building only on the flat surface. While a mobile robot is moving on the slanted surface, the view angle of LRF is dynamically changing, which makes it very difficult to build the 3D map using encoder data. To cope with this dynamic change of the view angle in build 3D map, IMU and balance filters are fused to correct the unstable encoder data in this research. Through the real navigation experiments, it is verified that the fusion of multiple sensors are properly performed to correct the slope angle of the slanted surface. The effectiveness of the balance filter are also checked through the hill climbing navigations.

• The Journal of Korea Robotics Society
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• v.12 no.1
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• pp.33-41
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• 2017

We present a region-based approach for accurate pose estimation of small mechanical components. Our algorithm consists of two key phases: Multi-view object co-segmentation and pose estimation. In the first phase, we explain an automatic method to extract binary masks of a target object captured from multiple viewpoints. For initialization, we assume the target object is bounded by the convex volume of interest defined by a few user inputs. The co-segmented target object shares the same geometric representation in space, and has distinctive color models from those of the backgrounds. In the second phase, we retrieve a 3D model instance with correct upright orientation, and estimate a relative pose of the object observed from images. Our energy function, combining region and boundary terms for the proposed measures, maximizes the overlapping regions and boundaries between the multi-view co-segmentations and projected masks of the reference model. Based on high-quality co-segmentations consistent across all different viewpoints, our final results are accurate model indices and pose parameters of the extracted object. We demonstrate the effectiveness of the proposed method using various examples.